CN106597240A - Insulator contamination monitoring system - Google Patents
Insulator contamination monitoring system Download PDFInfo
- Publication number
- CN106597240A CN106597240A CN201710059955.8A CN201710059955A CN106597240A CN 106597240 A CN106597240 A CN 106597240A CN 201710059955 A CN201710059955 A CN 201710059955A CN 106597240 A CN106597240 A CN 106597240A
- Authority
- CN
- China
- Prior art keywords
- module
- insulator
- neural network
- network prediction
- temperature
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1227—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials
- G01R31/1245—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of line insulators or spacers, e.g. ceramic overhead line cap insulators; of insulators in HV bushings
Landscapes
- Chemical & Material Sciences (AREA)
- Engineering & Computer Science (AREA)
- Ceramic Engineering (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Insulators (AREA)
- Testing Relating To Insulation (AREA)
Abstract
The invention discloses an insulator contamination monitoring system. An ultraviolet detection module, a temperature detection module and a humidity detection module are arranged to detect a contamination ultraviolet discharge signal of an insulator and the temperature and humidity of the environment where the insulator is placed respectively and input the ultraviolet discharge signal and temperature and humidity signals to a BP neural network prediction module. The BP neural network prediction module gives a predicted value of equivalent salt deposit density. The predicted value of equivalent salt deposit density is sent out through a wireless sending module under the control of a controller module. In a monitor room, a wireless receiving module receives the equivalent salt deposit density data. The staff checks and monitors the equivalent salt deposit density data at a PC monitoring side. Insulator flashover is prevented by predicting the equivalent salt deposit density. The insulator contamination monitoring system is predictive and practical.
Description
Technical field
The present invention relates to high-tension line monitoring, and in particular to insulator pollution monitoring system.
Background technology
Insulator is one of important component part in transmission line of electricity, is also the maximum device of usage amount.For connecting wire
With shaft tower, and make between wire and wire, wire and shaft tower insulate.The electric property of insulator is easily by the shadow of surface filth
Ring, produce failure, any one insulator string produces failure, can all affect the safe operation of transmission line of electricity, even results in whole line
The long-time on road, large-area power-cuts, the production development of safe operation, industrial or agricultural to whole power system and the day of town dweller
Often life causes tremendous influence.
Existing insulator pollution monitoring system, the output signal of the terminal of insulator of directly sampling, is filtered, amplitude
After comparison, counting, active rectification, operation amplifier etc. are processed, it is input into controller, pollution severity of insulators is judged by controller
Discharge scenario, directly goes the terminal output signal of insulator as characteristic quantity, can only directly judge the discharge scenario of filth, not
Information of forecasting can be given, when data exception is monitored, the good opportunity for cleaning insulator has often been missed, such insulator is dirty
Dirty monitoring system lacks practicality.
The content of the invention
The present invention provides insulator pollution monitoring system, and solve existing insulator pollution monitoring system presence does not possess pre-
The property surveyed, causes to lack the problem of practicality.
The present invention solves the above problems by the following technical programs：
Insulator pollution monitoring system, including ultraviolet light detection module, temperature detecting module, humidity detecting module, BP be refreshing
Jing neural network forecast modules, controller module, wireless sending module, wireless receiving module and PC monitoring clients；
The output end of the ultraviolet light detection module is connected with the input all the way of BP neural network prediction module；The temperature
The output end of degree detection module is connected with another road input of BP neural network prediction module；The humidity detecting module it is defeated
Go out end to be connected with the another road output end of BP neural network prediction module；The output end of the BP neural network prediction module and control
Device module processed is connected；The controller module be connected with wireless sending module；The wireless sending module and wireless receiving mould
Block is wirelessly connected；The wireless receiving module is connected with PC monitoring clients.
Further, also including at least one full skirt, the full skirt is installed on transmission line, for blocking insulator, is subtracted
Few filthy attachment is on the insulator；
The full skirt is fixedly provided with installed part, the ultraviolet light detection module, temperature detecting module, humidity detecting module,
BP neural network prediction module, controller module and wireless sending module are arranged in the installed part.
Further, the ultraviolet light detection module mainly includes ultraviolet light transducer, the ultraviolet light transducer detection
Insulator EUV discharge signal, and by the EUV discharge signal input to BP neural network prediction module.
Further, the temperature detecting module is temperature sensor, ring residing for the temperature sensor detection insulator
The temperature in border, the temperature signal is input into BP neural network prediction module.
Further, the humidity detecting module is humidity sensor, ring residing for the humidity sensor detection insulator
The humidity in border, the moisture signal is input into BP neural network prediction module.
Compared with prior art, with following features：
Ultraviolet light detection module, temperature detecting module and humidity detecting module are set, detect that insulator contamination is ultraviolet respectively
The humiture of discharge signal, insulator local environment, and EUV discharge signal and temperature-humidity signal are input into BP neural network
Prediction module, provides the predicted value of equivalent salt deposit density, and under the control of controller module, is sent by wireless sending module
Go out, in Control Room, wireless receiving module receives the equivalent salt deposit density data, and staff checks, monitors in PC monitoring clients,
Prevent insulator that flashover occurs by predicting equivalent salt deposit density so that the present invention possesses predictability, with more practicality.
Description of the drawings
Fig. 1 is present configuration theory diagram.
Specific embodiment
With reference to embodiments the invention will be further described, but the invention is not limited in these embodiments.
Insulator pollution monitoring system, including ultraviolet light detection module, temperature detecting module, humidity detecting module, BP be refreshing
Jing neural network forecast modules, controller module, wireless sending module, wireless receiving module and PC monitoring clients；The ultraviolet light inspection
The output end for surveying module is connected with the input all the way of BP neural network prediction module；The output end of the temperature detecting module with
Another road input of BP neural network prediction module is connected；The output end of the humidity detecting module is predicted with BP neural network
The another road output end of module is connected；The output end of the BP neural network prediction module is connected with controller module；The control
Device module processed be connected with wireless sending module；The wireless sending module is wirelessly connected with wireless receiving module；It is described wireless
Receiver module is connected with PC monitoring clients.
The ultraviolet light detection module mainly includes ultraviolet light transducer, and the ultraviolet light transducer detects insulator contamination
EUV discharge signal, and by the EUV discharge signal input to BP neural network prediction module.UV sensor utilizes light
Quick element, measurable electric signal is converted to by photovoltaic mode and guided optical mode by the UV signal that insulator contamination sends,
And the electric signal is input into into BP neural network prediction module.
The temperature detecting module is temperature sensor, and the temperature sensor detects the temperature of insulator local environment,
The temperature signal is input into BP neural network prediction module.Temperature sensor senses the temperature of insulator local environment, and turns
Electric signal is changed to, the electric signal is input into into BP neural network prediction module.
The humidity detecting module is humidity sensor, and the humidity sensor detects the humidity of insulator local environment,
The moisture signal is input into BP neural network prediction module.Humidity sensor senses the humidity of insulator local environment, and turns
Electric signal is changed to, the electric signal is input into into BP neural network prediction module.
Equivalent salt deposit density be and on insulator surface area every square centimeter adhere to filth in conductive materials content phase
When sodium chloride number, it can well characterize the pollution level of insulator surface, and the requirement to personnel and equipment is also very low, technology
On be easier to realize, therefore equivalent salt deposit density is comparatively ideal insulator dirty degree characteristic quantity.
The EUV discharge signal of insulator contamination can react the change of equivalent salt deposit density, and humidity can be to EUV discharge signal
Impact is produced, and there is certain association in temperature and humidity, therefore, by residing for the ultraviolet anti-electric signal of insulator contamination, insulator
The humiture of environment as BP neural network prediction module input signal, for judging insulator equivalent salt density.
BP neural network prediction module establishes three Internets, input layer, hidden layer and output layer.Input layer is three defeated
Enter signal, i.e. EUV discharge signal, temperature signal and moisture signal, hidden layer enters line activating, output layer using S type activation primitives
Output equivalent salt deposit density, using linear activation primitive line activating is entered, and three input letters are monitored and obtained to quota sample insulator
Number it is normalized as sample and model training.During practical application, three monitoring signals are input into pre- to BP neural network
Module is surveyed, BP neural network prediction module directly gives the equivalent salt deposit density value of prediction.
At least one full skirt is further included, the full skirt is installed on transmission line, for blocking insulator, reduce dirty
Dirty attachment on the insulator, extends the useful life of insulator.The full skirt is fixedly provided with installed part, and the ultraviolet light detects mould
Block, temperature detecting module, humidity detecting module, BP neural network prediction module, controller module and wireless sending module are installed
In the installed part, each module of maintenance is normal, stable operation.
The present invention the course of work be：Ultraviolet light detection module obtains the EUV discharge signal of insulator contamination, temperature inspection
The temperature signal that module obtains insulator local environment is surveyed, humidity detecting module obtains the moisture signal of insulator local environment,
Three signal inputs provide the equivalent salt deposit density of prediction to BP neural network prediction module by BP neural network prediction module
Value, the equivalence is perfunctory to density value under the control of controller module, and Jing wireless sending modules are sent into wireless receiving module, and
PC monitoring clients are finally-transmitted to, staff obtains the equivalent salt deposit density predicted value of each insulator contamination, root in PC monitoring clients
It is predicted that value is taken action in time, it is to avoid insulator is because of the operation of filthy impact power system.
Claims (5)
1. insulator pollution monitoring system, it is characterised in that：
Including ultraviolet light detection module, temperature detecting module, humidity detecting module, BP neural network prediction module, controller mould
Block, wireless sending module, wireless receiving module and PC monitoring clients；
The output end of the ultraviolet light detection module is connected with the input all the way of BP neural network prediction module；The temperature inspection
The output end for surveying module is connected with another road input of BP neural network prediction module；The output end of the humidity detecting module
It is connected with the another road output end of BP neural network prediction module；The output end and controller of the BP neural network prediction module
Module is connected；The controller module be connected with wireless sending module；The wireless sending module and wireless receiving module without
Line is connected；The wireless receiving module is connected with PC monitoring clients.
2. insulator pollution monitoring system according to claim 1, it is characterised in that：
At least one full skirt is further included, the full skirt is installed on transmission line, for blocking insulator, reduce filthy attached
On the insulator；
The full skirt is fixedly provided with installed part, and the ultraviolet light detection module, temperature detecting module, humidity detecting module, BP are refreshing
Jing neural network forecast modules, controller module and wireless sending module are arranged in the installed part.
3. insulator pollution monitoring system according to claim 1, it is characterised in that：
The ultraviolet light detection module mainly includes ultraviolet light transducer, and the ultraviolet light transducer detection insulator contamination is ultraviolet
Discharge signal, and by the EUV discharge signal input to BP neural network prediction module.
4. insulator pollution monitoring system according to claim 1, it is characterised in that：
The temperature detecting module is temperature sensor, and the temperature sensor detects the temperature of insulator local environment, described
Temperature signal is input into BP neural network prediction module.
5. insulator pollution monitoring system according to claim 1, it is characterised in that：
The humidity detecting module is humidity sensor, and the humidity sensor detects the humidity of insulator local environment, described
Moisture signal is input into BP neural network prediction module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710059955.8A CN106597240A (en) | 2017-01-24 | 2017-01-24 | Insulator contamination monitoring system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710059955.8A CN106597240A (en) | 2017-01-24 | 2017-01-24 | Insulator contamination monitoring system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106597240A true CN106597240A (en) | 2017-04-26 |
Family
ID=58585336
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710059955.8A Pending CN106597240A (en) | 2017-01-24 | 2017-01-24 | Insulator contamination monitoring system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106597240A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107462817A (en) * | 2017-08-04 | 2017-12-12 | 钱克猷 | With the temperature of filth, the method for the filthy state of water content detection insulator |
| CN113125908A (en) * | 2021-04-16 | 2021-07-16 | 华北电力大学 | Insulator contamination degree diagnosis device and detection method thereof |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2009016317A (en) * | 2007-07-09 | 2009-01-22 | Kobe Steel Ltd | Monitoring system for electric facilities |
| CN201233385Y (en) * | 2007-08-31 | 2009-05-06 | 重庆朗普科技有限公司 | Insulator dirt on-line detecting instrument |
| CN101661076A (en) * | 2009-09-04 | 2010-03-03 | 重庆大学 | Method for detecting pollution grade of insulator |
| CN102543258A (en) * | 2011-10-24 | 2012-07-04 | 桂林师范高等专科学校 | Environmentally-friendly and innocuous polycrystalline silicon solar energy battery back electric field slurry containing phosphorus and preparation method thereof |
| CN103411970A (en) * | 2013-07-17 | 2013-11-27 | 同济大学 | Alternating current transmission line insulator contamination condition detection method based on infrared thermography |
| CN203465377U (en) * | 2013-05-14 | 2014-03-05 | 三峡大学 | Solar-blind ultraviolet detection technology-based insulator deterioration detection device |
| CN103743648A (en) * | 2013-12-19 | 2014-04-23 | 西安工程大学 | Optical wave-based transmission line equivalent salt deposit density sensor and online measurement method thereof |
| CN103777125A (en) * | 2014-02-20 | 2014-05-07 | 福建汇兴智能化科技有限公司 | Pollution flashover detection device and method |
| CN104237467A (en) * | 2014-09-22 | 2014-12-24 | 国家电网公司 | Online monitoring system for state of insulator contamination |
| CN104616060A (en) * | 2014-12-23 | 2015-05-13 | 南京工程学院 | Method for predicating contamination severity of insulator based on BP neural network and fuzzy logic |
| CN204903698U (en) * | 2015-04-29 | 2015-12-23 | 国家电网公司 | Insulator pollution flashover early warning device based on meteorological phenomena and neural network |
| CN105353236A (en) * | 2015-10-22 | 2016-02-24 | 钱克猷 | On-line remote detection method and device for detecting state of disc-type insulator |
| CN206892253U (en) * | 2017-01-24 | 2018-01-16 | 桂林师范高等专科学校 | Insulator pollution monitoring system |
-
2017
- 2017-01-24 CN CN201710059955.8A patent/CN106597240A/en active Pending
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2009016317A (en) * | 2007-07-09 | 2009-01-22 | Kobe Steel Ltd | Monitoring system for electric facilities |
| CN201233385Y (en) * | 2007-08-31 | 2009-05-06 | 重庆朗普科技有限公司 | Insulator dirt on-line detecting instrument |
| CN101661076A (en) * | 2009-09-04 | 2010-03-03 | 重庆大学 | Method for detecting pollution grade of insulator |
| CN102543258A (en) * | 2011-10-24 | 2012-07-04 | 桂林师范高等专科学校 | Environmentally-friendly and innocuous polycrystalline silicon solar energy battery back electric field slurry containing phosphorus and preparation method thereof |
| CN203465377U (en) * | 2013-05-14 | 2014-03-05 | 三峡大学 | Solar-blind ultraviolet detection technology-based insulator deterioration detection device |
| CN103411970A (en) * | 2013-07-17 | 2013-11-27 | 同济大学 | Alternating current transmission line insulator contamination condition detection method based on infrared thermography |
| CN103743648A (en) * | 2013-12-19 | 2014-04-23 | 西安工程大学 | Optical wave-based transmission line equivalent salt deposit density sensor and online measurement method thereof |
| CN103777125A (en) * | 2014-02-20 | 2014-05-07 | 福建汇兴智能化科技有限公司 | Pollution flashover detection device and method |
| CN104237467A (en) * | 2014-09-22 | 2014-12-24 | 国家电网公司 | Online monitoring system for state of insulator contamination |
| CN104616060A (en) * | 2014-12-23 | 2015-05-13 | 南京工程学院 | Method for predicating contamination severity of insulator based on BP neural network and fuzzy logic |
| CN204903698U (en) * | 2015-04-29 | 2015-12-23 | 国家电网公司 | Insulator pollution flashover early warning device based on meteorological phenomena and neural network |
| CN105353236A (en) * | 2015-10-22 | 2016-02-24 | 钱克猷 | On-line remote detection method and device for detecting state of disc-type insulator |
| CN206892253U (en) * | 2017-01-24 | 2018-01-16 | 桂林师范高等专科学校 | Insulator pollution monitoring system |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107462817A (en) * | 2017-08-04 | 2017-12-12 | 钱克猷 | With the temperature of filth, the method for the filthy state of water content detection insulator |
| CN113125908A (en) * | 2021-04-16 | 2021-07-16 | 华北电力大学 | Insulator contamination degree diagnosis device and detection method thereof |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101614602B (en) | Method and device for monitoring power transmission line | |
| CN204330025U (en) | Overground cable security of operation online monitoring system | |
| KR102309900B1 (en) | The iot-based contactless lightning arrester diagnostic device and its management system using the device | |
| CN201773080U (en) | Insulator contamination online monitoring system | |
| CN104237467A (en) | Online monitoring system for state of insulator contamination | |
| CN105334811A (en) | Wireless tower monitoring method of power lines based on ZigBee network | |
| CN105510525A (en) | Electric-transmission-line dirt monitoring apparatus and method | |
| CN101929972A (en) | Insulator contamination on-line monitoring system | |
| CN105422181B (en) | Underground floods alarm method based on image and flood monitoring | |
| CN212083634U (en) | Transmission line insulator leakage current monitoring system | |
| US20230194592A1 (en) | Leakage and flashover current monitoring system in vhv overhead line insulators | |
| CN107515342A (en) | A kind of power distribution network outage analysis based on big data, early warning system | |
| CN110261750A (en) | The pollution flashover monitoring device and method of transmission circuit insulator string | |
| CN201233385Y (en) | Insulator dirt on-line detecting instrument | |
| CN112684517A (en) | Remote monitoring device for working environment of live working | |
| CN102879050A (en) | Water level and temperature online monitoring system for direct current grounding electrode detection well | |
| CN106597240A (en) | Insulator contamination monitoring system | |
| CN206892253U (en) | Insulator pollution monitoring system | |
| CN112363029A (en) | Equipment corona discharge online monitoring system and monitoring method thereof | |
| CN115389872A (en) | Handheld switch cabinet partial discharge polling instrument based on capacitive coupling method and method thereof | |
| CN103323056B (en) | A kind of power equipment DC current temperature, pressure monitoring device | |
| CN204439130U (en) | A kind of transmission line status on-line monitoring system | |
| CN202748054U (en) | Power line ice coating on-line monitoring system | |
| CN107728025A (en) | A kind of system for monitoring high-tension switch cabinet shelf depreciation on-line | |
| CN207424175U (en) | A kind of system for monitoring high-tension switch cabinet shelf depreciation on-line |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20170426 |
|
| WD01 | Invention patent application deemed withdrawn after publication |